Prompt-rag: Pioneering Vector Embedding-free Retrieval-augmented Generation In Niche Domains, Exemplified By Korean Medicine

Abstract

We propose a natural language prompt-based retrieval augmented generation (Prompt-RAG), a novel approach to enhance the performance of generative large language models (LLMs) in niche domains. Conventional RAG methods mostly require vector embeddings, yet the suitability of generic LLM-based embedding representations for specialized domains remains uncertain. To explore and exemplify this point, w